a powerful toolset for genome arithmetic — bedtools 2.31.0 documentation (original) (raw)
Tutorial¶
- We have developed a fairly comprehensive tutorial that demonstrates both the basics, as well as some more advanced examples of how bedtools can help you in your research. Please have a look.
- Robert Aboukhalil has developed sandbox.bio an excellent, web-based playground for the bedtools tutorial and other widely-used genomics tools.
Important notes¶
- As of version 2.28.0, bedtools now supports the CRAM format via the use of htslib. Specify the reference genome associated with your CRAM file via the CRAM_REFERENCE environment variable. Bedtools will look for this environment variable when it needs to access sequence data from the CRAM file (e.g., bamtofastq).
- With the exception of BAM files, bedtools assumes all input files are TAB delimited.
- bedtools also assumes that all input files use UNIX line endings.
- Unless you use the -sorted option, bedtools currently does not support chromosomes larger than 512Mb
- When using the -sorted option with files whose chromosomes are not lexicographically sorted (e.g., sort -k1,1 -k2,2n for BED files), one must provide a genome file (-g) defining the expected chromosome order.
- bedtools requires that chromosome naming schemes are identical in files that you are comparing (e.g., ‘chr1’ in one file and ‘1’ in another won’t work).
- .fai files may be used as genome (-g) files.
Performance¶
As of version 2.18, bedtools is substantially more scalable thanks to improvements we have made in the algorithm used to process datasets that are pre-sorted by chromosome and start position. As you can see in the plots below, the speed and memory consumption scale nicely with sorted data as compared to the poor scaling for unsorted data. The current version of bedtools intersect is as fast as (or slightly faster) than the bedops package’s bedmap which uses a similar algorithm for sorted data. The plots below represent counting the number of intersecting alignments from exome capture BAM files against CCDS exons. The alignments have been converted to BED to facilitate comparisons to bedops. We compare to the bedmap --ec option because similar error checking is enforced by bedtools.
Note: bedtools could not complete when using 100 million alignments and the R-Tree algorithm used for unsorted data owing to a lack of memory.
Commands used:
bedtools sorted
$ bedtools intersect
-a ccds.exons.bed -b aln.bam.bed
-c
-sorted
bedtools unsorted
$ bedtools intersect
-a ccds.exons.bed -b aln.bam.bed
-c
bedmap (without error checking)
$ bedmap --echo --count --bp-ovr 1
ccds.exons.bed aln.bam.bed
bedmap (no error checking)
$ bedmap --ec --echo --count --bp-ovr 1
ccds.exons.bed aln.bam.bed
Brief example¶
Let’s imagine you have a BED file of ChiP-seq peaks from two different experiments. You want to identify peaks that were observed in both experiments (requiring 50% reciprocal overlap) and for those peaks, you want to find to find the closest, non-overlapping gene. Such an analysis could be conducted with two, relatively simple bedtools commands.
intersect the peaks from both experiments.
-f 0.50 combined with -r requires 50% reciprocal overlap between the
peaks from each experiment.
$ bedtools intersect -a exp1.bed -b exp2.bed -f 0.50 -r > both.bed
find the closest, non-overlapping gene for each interval where
both experiments had a peak
-io ignores overlapping intervals and returns only the closest,
non-overlapping interval (in this case, genes)
$ bedtools closest -a both.bed -b genes.bed -io > both.nearest.genes.txt
License¶
bedtools is freely available under a GNU Public License (Version 2).